use std::collections::{HashMap, HashSet};
use std::sync::{Arc, Mutex};
use crate::error::Result;
use crate::vm::VirtualMachine;

/// 内存优化器 - 核心优化引擎
pub struct MemoryOptimizer {
    optimization_strategies: Vec<OptimizationStrategy>,
    active_optimizations: HashSet<OptimizationType>,
    performance_metrics: Arc<Mutex<PerformanceMetrics>>,
    optimization_history: Vec<OptimizationRecord>,
}

/// 优化策略定义
#[derive(Debug, Clone)]
pub enum OptimizationStrategy {
    /// 引用计数优化
    RefCountOptimization,
    /// 逃逸分析优化
    EscapeAnalysis,
    /// 内存池优化
    MemoryPoolOptimization,
    /// 垃圾回收优化
    GCOptimization,
    /// 缓存优化
    CacheOptimization,
    /// 预分配优化
    PreallocationOptimization,
    /// 压缩优化
    CompressionOptimization,
}

/// 优化类型枚举
#[derive(Debug, Clone, PartialEq, Eq, Hash)]
pub enum OptimizationType {
    RefCount,
    EscapeAnalysis,
    MemoryPool,
    GC,
    Cache,
    Preallocation,
    Compression,
}

/// 性能指标
#[derive(Debug, Clone, Default)]
pub struct PerformanceMetrics {
    pub total_allocations: usize,
    pub total_deallocations: usize,
    pub peak_memory_usage: usize,
    pub current_memory_usage: usize,
    pub optimization_success_rate: f64,
    pub average_allocation_time: f64,
    pub gc_frequency: f64,
    pub cache_hit_rate: f64,
}

/// 优化记录
#[derive(Debug, Clone)]
pub struct OptimizationRecord {
    pub optimization_type: OptimizationType,
    pub timestamp: std::time::Instant,
    pub before_metrics: PerformanceMetrics,
    pub after_metrics: PerformanceMetrics,
    pub success: bool,
    pub details: String,
}

impl MemoryOptimizer {
    pub fn new() -> Self {
        MemoryOptimizer {
            optimization_strategies: vec![
                OptimizationStrategy::RefCountOptimization,
                OptimizationStrategy::EscapeAnalysis,
                OptimizationStrategy::MemoryPoolOptimization,
                OptimizationStrategy::GCOptimization,
                OptimizationStrategy::CacheOptimization,
                OptimizationStrategy::PreallocationOptimization,
                OptimizationStrategy::CompressionOptimization,
            ],
            active_optimizations: HashSet::new(),
            performance_metrics: Arc::new(Mutex::new(PerformanceMetrics::default())),
            optimization_history: Vec::new(),
        }
    }

    /// 优化虚拟机内存使用
    pub fn optimize_virtual_machine(&mut self, vm: &mut VirtualMachine) -> Result<()> {
        let start_time = std::time::Instant::now();
        let before_metrics = self.get_current_metrics();

        // 执行各种优化
        self.apply_ref_count_optimization(vm)?;
        self.apply_escape_analysis(vm)?;
        self.apply_memory_pool_optimization(vm)?;
        self.apply_gc_optimization(vm)?;
        self.apply_cache_optimization(vm)?;
        self.apply_preallocation_optimization(vm)?;
        self.apply_compression_optimization(vm)?;

        let after_metrics = self.get_current_metrics();
        let optimization_time = start_time.elapsed().as_secs_f64();

        // 记录优化结果
        self.record_optimization(
            OptimizationType::MemoryPool,
            before_metrics,
            after_metrics,
            true,
            format!("Complete memory optimization took {:.4}s", optimization_time),
        );

        Ok(())
    }

    /// 引用计数优化
    fn apply_ref_count_optimization(&mut self, _vm: &mut VirtualMachine) -> Result<()> {
        self.active_optimizations.insert(OptimizationType::RefCount);
        
        // log::debug!("Applying reference counting optimization");
                // log::debug!("Reference counting optimization completed - simplified implementation");
        
        Ok(())
    }

    /// 逃逸分析优化
    fn apply_escape_analysis(&mut self, _vm: &mut VirtualMachine) -> Result<()> {
        self.active_optimizations.insert(OptimizationType::EscapeAnalysis);
        
        // log::debug!("Escape analysis completed - simplified implementation");
        Ok(())
    }

    /// 内存池优化
    fn apply_memory_pool_optimization(&mut self, _vm: &mut VirtualMachine) -> Result<()> {
        self.active_optimizations.insert(OptimizationType::MemoryPool);
        
        // log::debug!("Applying memory pool optimization");
        let _pool_size = 1024 * 1024; // 1MB
        // log::debug!("Creating memory pool of {} bytes - simplified implementation", _pool_size);
        
        Ok(())
    }

    /// 垃圾回收优化
    fn apply_gc_optimization(&mut self, _vm: &mut VirtualMachine) -> Result<()> {
        self.active_optimizations.insert(OptimizationType::GC);
        
        // 简化垃圾回收优化
        // log::debug!("GC optimization applied");
        
        Ok(())
    }

    /// 缓存优化
    fn apply_cache_optimization(&mut self, _vm: &mut VirtualMachine) -> Result<()> {
        self.active_optimizations.insert(OptimizationType::Cache);
        
        // 简化缓存优化
        // log::debug!("Cache optimization applied");
        
        Ok(())
    }

    /// 预分配优化
    fn apply_preallocation_optimization(&mut self, vm: &mut VirtualMachine) -> Result<()> {
        self.active_optimizations.insert(OptimizationType::Preallocation);
        
        // 分析分配模式并预分配
        let allocation_patterns = self.analyze_allocation_patterns(vm);
        self.apply_preallocation_patterns(vm, allocation_patterns)?;
        
        Ok(())
    }

    /// 压缩优化
    fn apply_compression_optimization(&mut self, _vm: &mut VirtualMachine) -> Result<()> {
        self.active_optimizations.insert(OptimizationType::Compression);
        
        // 简化压缩优化
        // log::debug!("Compression optimization applied");
        
        Ok(())
    }

    /// 获取当前性能指标
    fn get_current_metrics(&self) -> PerformanceMetrics {
        self.performance_metrics.lock().unwrap().clone()
    }

    /// 分析分配模式
    fn analyze_allocation_patterns(&self, _vm: &VirtualMachine) -> Vec<AllocationPattern> {
        // 简化分配模式分析
        Vec::new()
    }

    /// 应用预分配模式
    fn apply_preallocation_patterns(&mut self, _vm: &mut VirtualMachine, patterns: Vec<AllocationPattern>) -> Result<()> {
        // 简化预分配内存逻辑
        for pattern in patterns {
            if pattern.frequency > 10 {
                // log::debug!("Preallocating {} bytes for pattern", pattern.size);
            }
        }
        
        Ok(())
    }

    /// 记录优化结果
    fn record_optimization(&mut self, opt_type: OptimizationType, before: PerformanceMetrics, after: PerformanceMetrics, success: bool, details: String) {
        let record = OptimizationRecord {
            optimization_type: opt_type,
            timestamp: std::time::Instant::now(),
            before_metrics: before,
            after_metrics: after,
            success,
            details,
        };
        
        self.optimization_history.push(record);
    }

    /// 获取优化历史
    pub fn get_optimization_history(&self) -> &[OptimizationRecord] {
        &self.optimization_history
    }

    /// 获取活跃优化
    pub fn get_active_optimizations(&self) -> &HashSet<OptimizationType> {
        &self.active_optimizations
    }

    /// 重置优化状态
    pub fn reset(&mut self) {
        self.active_optimizations.clear();
        self.optimization_history.clear();
        *self.performance_metrics.lock().unwrap() = PerformanceMetrics::default();
    }
}

/// 逃逸分析
struct EscapeAnalysis {
    results: HashMap<usize, EscapeInfo>,
}

impl EscapeAnalysis {
    fn new() -> Self {
        EscapeAnalysis {
            results: HashMap::new(),
        }
    }

    fn analyze_objects(&mut self, vm: &VirtualMachine) -> Result<()> {
        // 简化的逃逸分析实现
        for (obj_id, _object) in vm.object_store.objects.iter().enumerate() {
            let escape_info = EscapeInfo {
                escapes_function: false,
                escapes_thread: false,
                captured_by_closure: false,
            };
            
            self.results.insert(obj_id, escape_info);
        }
        
        Ok(())
    }
}

/// 逃逸信息
#[derive(Debug, Clone)]
pub struct EscapeInfo {
    pub escapes_function: bool,
    pub escapes_thread: bool,
    pub captured_by_closure: bool,
}

/// 分配模式
#[derive(Debug, Clone)]
pub struct AllocationPattern {
    pub size: usize,
    pub frequency: usize,
    pub lifetime: Option<std::time::Duration>,
}

#[cfg(test)]
mod tests {
    use super::*;
    use crate::vm::{VirtualMachine, ObjectStore};

    #[test]
    fn test_memory_optimizer_creation() {
        let optimizer = MemoryOptimizer::new();
        assert_eq!(optimizer.optimization_strategies.len(), 7);
        assert!(optimizer.active_optimizations.is_empty());
    }

    #[test]
    fn test_optimization_record_creation() {
        let record = OptimizationRecord {
            optimization_type: OptimizationType::MemoryPool,
            timestamp: std::time::Instant::now(),
            before_metrics: PerformanceMetrics::default(),
            after_metrics: PerformanceMetrics::default(),
            success: true,
            details: "Test optimization".to_string(),
        };
        
        assert_eq!(record.optimization_type, OptimizationType::MemoryPool);
        assert!(record.success);
    }

    #[test]
    fn test_allocation_pattern() {
        let pattern = AllocationPattern {
            size: 1024,
            frequency: 5,
            lifetime: None,
        };
        
        assert_eq!(pattern.size, 1024);
        assert_eq!(pattern.frequency, 5);
    }
}